{"title":"将统计森林反射率模型与Sentinel-2 MSI图像集成到连续森林清查系统中","authors":"A. Kuusk, Mait Lang","doi":"10.46490/bf467","DOIUrl":null,"url":null,"abstract":"Spectral signatures of forest stands in Sentinel-2 MSI spectral bands are simulated with the statistical forest reflectance (SFRM) model and compared to the spectral signatures measured in spectral images at ten study sites in Estonia. As an overall measure of the agreement between simulated and measured spectral signatures we used the total error calculated as the sum of relative errors over spectral bands B2 to B11 of Sentinel-2. The distribution of the total error has strongly positive skewness at all study sites and all types of forests (broadleaf, pine and spruce forests). The right tail of the distribution is low. The stands of high value of the total error far right in the tail of the distribution may have some errors in their inventory data, or the inventory data are outdated. Pertinent stands should have priority in their in situ checking process. The SFRM model is a simple and reliable tool for the validity checking of forest inventory data, using routinely collected forest inventory data and operational satellite information of moderate spatial resolution. The model is simple and computationally efficient. Preparing input data for the model is a simple query in the forest inventory database. The suggested procedure can be incorporated into the automated systems of continuous forest inventory. \n \nKeywords: Forest inventory, Sentinel-2 MSI images, Statistical forest reflectance model","PeriodicalId":55404,"journal":{"name":"Baltic Forestry","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integration of statistical forest reflectance model and Sentinel-2 MSI images into a continuous forest inventory system\",\"authors\":\"A. Kuusk, Mait Lang\",\"doi\":\"10.46490/bf467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spectral signatures of forest stands in Sentinel-2 MSI spectral bands are simulated with the statistical forest reflectance (SFRM) model and compared to the spectral signatures measured in spectral images at ten study sites in Estonia. As an overall measure of the agreement between simulated and measured spectral signatures we used the total error calculated as the sum of relative errors over spectral bands B2 to B11 of Sentinel-2. The distribution of the total error has strongly positive skewness at all study sites and all types of forests (broadleaf, pine and spruce forests). The right tail of the distribution is low. The stands of high value of the total error far right in the tail of the distribution may have some errors in their inventory data, or the inventory data are outdated. Pertinent stands should have priority in their in situ checking process. The SFRM model is a simple and reliable tool for the validity checking of forest inventory data, using routinely collected forest inventory data and operational satellite information of moderate spatial resolution. The model is simple and computationally efficient. Preparing input data for the model is a simple query in the forest inventory database. The suggested procedure can be incorporated into the automated systems of continuous forest inventory. \\n \\nKeywords: Forest inventory, Sentinel-2 MSI images, Statistical forest reflectance model\",\"PeriodicalId\":55404,\"journal\":{\"name\":\"Baltic Forestry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2020-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Baltic Forestry\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.46490/bf467\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Baltic Forestry","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.46490/bf467","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FORESTRY","Score":null,"Total":0}
Integration of statistical forest reflectance model and Sentinel-2 MSI images into a continuous forest inventory system
Spectral signatures of forest stands in Sentinel-2 MSI spectral bands are simulated with the statistical forest reflectance (SFRM) model and compared to the spectral signatures measured in spectral images at ten study sites in Estonia. As an overall measure of the agreement between simulated and measured spectral signatures we used the total error calculated as the sum of relative errors over spectral bands B2 to B11 of Sentinel-2. The distribution of the total error has strongly positive skewness at all study sites and all types of forests (broadleaf, pine and spruce forests). The right tail of the distribution is low. The stands of high value of the total error far right in the tail of the distribution may have some errors in their inventory data, or the inventory data are outdated. Pertinent stands should have priority in their in situ checking process. The SFRM model is a simple and reliable tool for the validity checking of forest inventory data, using routinely collected forest inventory data and operational satellite information of moderate spatial resolution. The model is simple and computationally efficient. Preparing input data for the model is a simple query in the forest inventory database. The suggested procedure can be incorporated into the automated systems of continuous forest inventory.
Keywords: Forest inventory, Sentinel-2 MSI images, Statistical forest reflectance model
期刊介绍:
The journal welcomes the original articles as well as short reports, review papers on forestry and forest science throughout the Baltic Sea region and elsewhere in the area of boreal and temperate forests. The Baltic Sea region is rather unique through its intrinsic environment and distinguished geographical and social conditions. A temperate climate, transitional and continental, has influenced formation of the mixed coniferous and deciduous stands of high productivity and biological diversity. The forest science has been affected by the ideas from both the East and West.
In 1995, Forest Research Institutes and Universities from Estonia, Latvia and Lithuania
joined their efforts to publish BALTIC FORESTRY.